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Analysis and inorganic composition of microplastics in commercial Malaysian fish meals

2019· article· en· W2984641305 on OpenAlexaff
Samaneh Karbalaei, Abolfazl Golieskardi, Dorothy Uning Watt, Mathieu Boiret, Parichehr Hanachi, Tony R. ‎Walker, Ali Karami

Bibliographic record

VenueMarine Pollution Bulletin · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsDalhousie University
FundersMinistry of Higher Education, Malaysia
KeywordsMicroplasticsComposition (language)Fish <Actinopterygii>Food scienceFish mealContaminationShellfishEnvironmental chemistryMealChemistryBiologyFisheryAquatic animalEcology

Abstract

fetched live from OpenAlex

Presence of microplastics (MPs) in a broad range of wild and cultured marine organisms is well-documented, but transfer mechanisms by which cultured organisms are contaminated with MPs is poorly understood. MP loads in three Malaysian commercial brands of fish meal were investigated. Chemical composition of extracted MP-like particles was confirmed using micro-Raman spectroscopy. Inorganic composition of MPs and pigment particles were assessed through energy-dispersive X-ray spectroscopy (EDX). Out of 336 extracted particles, 64.3% were plastic polymers, 25% pigment particles, 4.2% non-plastic items, and 6.5% were unidentified. Fragments were the dominant form of MPs (78.2%) followed by filaments (13.4%) and films (8.4%). This study demonstrates that cultured organisms could be exposed to high levels of MPs via MP contaminated fish/shellfish used in fish meal production. Fish meal replacement with other sources of protein including meat meals and plant-based meals may mitigate MP exposure to cultured or farmed organisms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.181
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations116
Published2019
Admission routes1
Has abstractno

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